Application of machine learning in CT images and X-rays of COVID-19 pneumonia. Issue 36 (10th September 2021)
- Record Type:
- Journal Article
- Title:
- Application of machine learning in CT images and X-rays of COVID-19 pneumonia. Issue 36 (10th September 2021)
- Main Title:
- Application of machine learning in CT images and X-rays of COVID-19 pneumonia
- Authors:
- Zhang, Fengjun
- Other Names:
- MacRae. Duncan A. section editor.
- Abstract:
- Abstract : Abstract: Coronavirus disease (COVID-19) has spread worldwide. X-ray and computed tomography (CT) are 2 technologies widely used in image acquisition, segmentation, diagnosis, and evaluation. Artificial intelligence can accurately segment infected parts in X-ray and CT images, assist doctors in improving diagnosis efficiency, and facilitate the subsequent assessment of the severity of the patient infection. The medical assistant platform based on machine learning can help radiologists make clinical decisions and helper in screening, diagnosis, and treatment. By providing scientific methods for image recognition, segmentation, and evaluation, we summarized the latest developments in the application of artificial intelligence in COVID-19 lung imaging, and provided guidance and inspiration to researchers and doctors who are fighting the COVID-19 virus.
- Is Part Of:
- Medicine. Volume 100:Issue 36(2021)
- Journal:
- Medicine
- Issue:
- Volume 100:Issue 36(2021)
- Issue Display:
- Volume 100, Issue 36 (2021)
- Year:
- 2021
- Volume:
- 100
- Issue:
- 36
- Issue Sort Value:
- 2021-0100-0036-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-09-10
- Subjects:
- coronavirus disease 2019 -- computed tomography -- machine learning -- X-ray
Medicine -- Periodicals
Medicine -- Periodicals
Médecine -- Périodiques
Geneeskunde
Medicine
Periodicals
Periodicals
610.5 - Journal URLs:
- http://journals.lww.com/md-journal/pages/default.aspx ↗
http://gateway.ovid.com/ovidweb.cgi?T=JS&PAGE=toc&D=ovft&MODE=ovid&NEWS=N&AN=00002060-000000000-00000 ↗
http://journals.lww.com ↗ - DOI:
- 10.1097/MD.0000000000026855 ↗
- Languages:
- English
- ISSNs:
- 0025-7974
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5534.000000
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British Library STI - ELD Digital store - Ingest File:
- 24958.xml